Efficient Algorithms Based on Relational Queries to Mine Frequent Graphs
Frequent sub-graph mining is an important problem in data mining with wide application in science. For instance, graphs can be used to represent structural relationships in problems related to network topology, chemical compound, protein structures, and so on. Searching for patterns from graph databases is difficult since graph-related operations generally have higher time complexity than equivalent operations on frequent item-sets. From a practical standpoint, databases keep growing with lots of opportunities and need to mine graphs. Even though there is a significant body of work on graph mining, most techniques work outside the database system.